Examination of Significant Factors Influencing Response Time of Customer Complaint Based on Analytics Method
Hafizah Farhah Saipan Saipol1, Nur Tasnim Shamsuddin2, Zaihisma Che Cob3, Nur Laila Ab Ghani4, Sulfeeza Mohd Drus5
1Hafizah Farhah Saipan Saipol*, Institute of Informatics and Computing in Energy, University Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor.
2Nur Tasnim Shamsuddin, UNITEN Research and Development, Jalan IKRAM-UNITEN, Kajang, Selangor.
3Zaihisma Che Cob, College of Computing and Informatics, University Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor.
4Nur Laila Ab Ghani, College of Computing and Informatics, University Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor.
5Sulfeeza Mohd Drus, College of Computing and Informatics, University Tenaga Nasional, Jalan IKRAM-UNITEN, Kajang, Selangor.
Manuscript received on September 01, 2019. | Revised Manuscript received on September 22, 2019. | Manuscript published on October 30, 2019. | PP: 3415-3418 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2642109119/2019©BEIESP | DOI: 10.35940/ijeat.A2642.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The purpose of this study is to investigate significant factors that influenced duration of solving financial institutions’ customer complaint. Using raw customer complaint dataset from Consumer Financial Protection Bureau (CFPB) website, it was found that many of sub-categories are not well organized. Thus, it is important to proceed with data cleaning and data preparation steps before any analysis been performed. In this study, Artificial Neural Network (ANN) had been chosen since it can deal with non-linear relationship by using sigmoid function. Further to this, it was found that Product, Company response and Issues are the significant factors that are more likely to be solved more than one day. The use of this analysis can be particularly beneficial for related financial party that might need to assist their customer in future.
Keywords: Customer Complaint, Neural Network, Data Cleaning.